@conference {2580,
	title = {GOM-Based Compatible Substitutions Optimization for Variable-Length Representation Gray-Box Problems},
	booktitle = {Genetic and Evolutionary Computation Conference (GECCO {\textquoteright}25 Companion)},
	year = {2025},
	publisher = {ACM},
	organization = {ACM},
	abstract = {Effective recombination operators utilizing interdependence of genes ensure that specific arrangements or combinations of genes are preserved, allowing offspring to inherit beneficial traits from both parents without disrupting important gene interactions. However, such operators are easiest to implement for fixed-length genetic representations such as vectors of genes. In this work, we show that for some problems with variable-length representations, it is possible to design an algorithm that employs the GOM (Gene-pool Optimal Mixing) operator without the need to learn dependencies between specific genes. Instead, our approach - Compatible Substitutions Optimization (CoSO) - leverages expert-driven models of compatible substitutions that take advantage of the characteristics of the representation. Our experiments indicate that the proposed method performs better than standard evolutionary algorithms on a problem of evolving tall 3D structures, while also providing significant potential for further enhancements.},
	doi = {10.1145/3712255.3726717},
	url = {http://www.framsticks.com/files/common/GOM-BasedCompatibleSubstitutionsOptimization.pdf},
	author = {Maciej Komosinski and Konrad Miazga}
}
@article {Komosinski-and-Ulatowski-2004,
	title = {Genetic mappings in artificial genomes},
	journal = {Theory in Biosciences},
	volume = {123},
	number = {2},
	year = {2004},
	month = {September},
	pages = {125{\textendash}137},
	abstract = {This paper concerns processing of genomes of artificial (computer-simulated) organisms. Of special interest is the process of translation of genotypes into phenotypes, and utilizing the mapping information obtained during such translation. If there exists more than one genetic encoding in a single artificial life model, then the translation may also occur between different encodings. The obtained mapping information allows to present genes-phenes relationships visually and interactively to a person, in order to increase understanding of the genotype-to-phenotype translation process and genetic encoding properties. As the mapping associates parts of the source sequence with the translated destination, it may be also used to trace genes, phenes, and their relationships during simulated evolution. 

A mappings composition procedure is formally described, and a simple method of visual mapping presentation is established. Finally, advanced visualizations of gene-phene relationships are demonstrated as practical examples of introduced techniques. These visualizations concern genotypes expressed in various encodings, including an encoding which exhibits polygenic and pleiotropic properties.},
	doi = {10.1016/j.thbio.2004.04.002},
	url = {http://www.framsticks.com/files/common/GeneticMappingsInArtificialGenomes.pdf},
	author = {Maciej Komosinski and Szymon Ulatowski}
}
